# Week 2

 Fluctuation of the value of a statistic from one sample from a population to another sample. Sampling error Theoretical distribution of a statistic using an infinite number of samples as a basis and the values of the statistic used in the distribution. Sampling distribution Theoretical distribution of an infinite number of means of samples. Sampling distribution of the mean Standard deviation of the infinite number of means in the sampling distribution of the mean. Standard error of the mean Statistical estimation using information from a sample to estimate a single statistic to represent a population parameter. Point estimation Range of values within which a population parameter is estimated to lie. Confidence interval Hypothesis that states there is no relationship between the variables of interest. Null hypothesis Hypothesis that states there is a relationship between variables of interest. Alternate hypothesis Error created when rejecting the null hypothesis when it is actually true. Type I error Error created when accepting the null hypothesis when it is actually false. Type II error Level designating the established risk of committing a type I error. Alpha level The probability of committing a type II error. Beta The probability of correctly rejecting a false null hypothesis. Power Statistical tests that involve assumptions about variable distribution, estimation of a parameter, and use of scale measures. Parametric tests Class of inferential statistics that do not make assumptions about variable distribution. Non-parametric tests Test of statistical significance in which only values at one extreme of a distribution are considered in determining significance. One-tailed test Test of statistical significance in which values at both extremes of a distribution are considered in determining significance. Two-tailed test Area of the sampling distribution representing values which are “improbable” if the null hypothesis is true. Critical region Concept representing the number of things free to vary about a parameter. A way to take sample size into consideration. Degrees of freedom Test to evaluate the probability that the value of the sample mean equals that of population mean. One-sample t-test Standard deviation of the difference between sample distribution means and that of the population mean. Standard error of the difference Test to determine the probability that the means of two groups are equal, when the groups are independent of each other. Independent groups t-test Test to determine the probability that paired means are equal; two groups/measurements are tested to determine if they differ. Paired t-test Index of the magnitude and direction of the relationship between a continuous variable and a dichotomous variable. Point biserial correlation Procedure for testing mean differences among three or more groups by comparing the variability between groups with that within the groups. Analysis of Variance (ANOVA) Variability arising from group differences in ANOVA. Between-group variance Variability arising between subjects in groups in ANOVA. Within-group variance Statistic in which variation attributable to different sources (e.g., between and within groups) is compared. F ratio Sum of squared deviation scores. Sum of squares Analysis of variance used to test the relationship between one independent variable and a dependent variable. One-way ANOVA Analysis of variance used to test the relationship between two or more independent variables and a dependent variable simultaneously. Multifactorial ANOVA Procedure for testing mean differences in a within-subject design with three or more conditions/observation periods. Repeated measures ANOVA Test for comparing all possible pairs of groups following a significant result of overall group differences (e.g., a significant ANOVA result). post hoc test AuthorFlawlessEra ID22495 Card SetWeek 2 DescriptionWeek 2 vocabulary Updated2010-06-07T22:12:59Z Show Answers